Finding experiments

To use incense we first have to instantiate an experiment loader that will enable us to query the database for specific runs.

targets_type iteration autoencoder_type batch_size artifacts
exp_id
9 Mnist False normal_dim 256 {'history_autoencoder': Artifact(name=history_...
10 Mnist False normal_dim 128 {'history_autoencoder': Artifact(name=history_...
11 Mnist False normal_dim 64 {'history_autoencoder': Artifact(name=history_...
12 Mnist False normal_dim 32 {'history_autoencoder': Artifact(name=history_...
13 10_Targets False normal_dim 256 {'history_autoencoder': Artifact(name=history_...
14 10_Targets False normal_dim 128 {'history_autoencoder': Artifact(name=history_...
15 10_Targets False normal_dim 64 {'history_autoencoder': Artifact(name=history_...
16 10_Targets False normal_dim 32 {'history_autoencoder': Artifact(name=history_...
70 Noisy False normal_dim 256 {'history_autoencoder': Artifact(name=history_...
71 Noisy False normal_dim 128 {'history_autoencoder': Artifact(name=history_...
72 Noisy False normal_dim 64 {'history_autoencoder': Artifact(name=history_...
73 Noisy False normal_dim 32 {'history_autoencoder': Artifact(name=history_...
targets_type iteration autoencoder_type batch_size artifacts sort
exp_id
13 10_Targets False normal_dim 256 {'history_autoencoder': Artifact(name=history_... 0
14 10_Targets False normal_dim 128 {'history_autoencoder': Artifact(name=history_... 1
15 10_Targets False normal_dim 64 {'history_autoencoder': Artifact(name=history_... 2
16 10_Targets False normal_dim 32 {'history_autoencoder': Artifact(name=history_... 3
9 Mnist False normal_dim 256 {'history_autoencoder': Artifact(name=history_... 4
10 Mnist False normal_dim 128 {'history_autoencoder': Artifact(name=history_... 5
11 Mnist False normal_dim 64 {'history_autoencoder': Artifact(name=history_... 6
12 Mnist False normal_dim 32 {'history_autoencoder': Artifact(name=history_... 7
70 Noisy False normal_dim 256 {'history_autoencoder': Artifact(name=history_... 8
71 Noisy False normal_dim 128 {'history_autoencoder': Artifact(name=history_... 9
72 Noisy False normal_dim 64 {'history_autoencoder': Artifact(name=history_... 10
73 Noisy False normal_dim 32 {'history_autoencoder': Artifact(name=history_... 11

Red best overall, and also best of subset. Bes means for accuracy max, rest min. Green best of subset.

predictions_df_0
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.9815 0.9812 0.9823 0.9828 0.9702 0.9754 0.9788 0.9745 0.9623 0.964 0.9646 0.9626
1 0.979 0.9785 0.979 0.9808 0.9661 0.9715 0.9733 0.97 0.9516 0.9508 0.9509 0.9502
2 0.9787 0.9783 0.888 0.9798 0.9553 0.9628 0.9641 0.9619 0.9357 0.9347 0.9308 0.929
3 0.9787 0.9782 0.8866 0.9797 0.9383 0.9487 0.9474 0.9487 0.9179 0.9142 0.9072 0.9074
4 0.9787 0.9782 0.8866 0.9797 0.9137 0.9341 0.9255 0.9308 0.9036 0.896 0.8874 0.8886
5 0.9787 0.9782 0.8866 0.9797 0.889 0.9173 0.9028 0.9085 0.8915 0.8805 0.8694 0.869
6 0.9787 0.9782 0.8866 0.9797 0.8614 0.8962 0.8784 0.886 0.8793 0.8638 0.8518 0.8506
7 0.9787 0.9782 0.8866 0.9797 0.8336 0.8731 0.8543 0.8586 0.8676 0.849 0.836 0.8357
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.406183 0.408179 0.407608 0.407474 0.024755 0.0234812 0.0269704 0.0282939 0.654313 0.654617 0.65577 0.656995
1 0.411457 0.412459 0.40965 0.411199 0.0367421 0.0336826 0.0382817 0.0413423 0.669885 0.670316 0.67213 0.674791
2 0.41221 0.412886 0.417009 0.411752 0.0519603 0.0463235 0.0523998 0.0571439 0.68408 0.684528 0.687386 0.691021
3 0.412308 0.41294 0.429275 0.411833 0.0691046 0.0604308 0.0680922 0.0742471 0.696456 0.696987 0.701096 0.705155
4 0.412308 0.412948 0.429394 0.411838 0.0870761 0.0752679 0.0847133 0.0917471 0.707273 0.707905 0.713419 0.717449
5 0.412308 0.412948 0.429395 0.411838 0.10516 0.0903165 0.101343 0.109174 0.716811 0.717543 0.724535 0.728261
6 0.412308 0.412948 0.429395 0.411838 0.122949 0.105218 0.117771 0.126145 0.725304 0.72611 0.734668 0.737908
7 0.412308 0.412948 0.429395 0.411838 0.140185 0.119773 0.133901 0.142931 0.732967 0.733786 0.743981 0.746582
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.266431 0.266991 0.266421 0.266433 0.0497662 0.0480546 0.0517474 0.053198 0.376717 0.377687 0.379944 0.38026
1 0.267329 0.26793 0.267278 0.267102 0.0596667 0.0567758 0.0609211 0.0638463 0.38577 0.387085 0.38969 0.390295
2 0.26748 0.268034 0.272747 0.267218 0.0706438 0.0662624 0.071089 0.0751611 0.393433 0.395008 0.398159 0.398923
3 0.267497 0.268044 0.276986 0.267242 0.0819333 0.0759058 0.0814678 0.0863705 0.400082 0.401848 0.405675 0.406408
4 0.267496 0.268046 0.277031 0.267243 0.0930401 0.0853716 0.0917694 0.0971769 0.405892 0.407802 0.412383 0.412935
5 0.267496 0.268046 0.277031 0.267243 0.103745 0.0945215 0.101642 0.107506 0.41102 0.413017 0.418404 0.418679
6 0.267496 0.268046 0.277031 0.267243 0.113953 0.103277 0.111095 0.117276 0.415592 0.417621 0.423873 0.423788
7 0.267496 0.268046 0.277031 0.267243 0.12364 0.111615 0.120138 0.126696 0.41972 0.421727 0.42888 0.428383 
predictions_df_10
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.9702 0.9703 0.9725 0.9737 0.9437 0.9484 0.9534 0.9539 0.96 0.9592 0.9593 0.957
1 0.9673 0.967 0.9702 0.9728 0.9464 0.9546 0.9555 0.9558 0.9504 0.9504 0.9462 0.9441
2 0.9673 0.9669 0.8816 0.9723 0.9296 0.9418 0.9388 0.9416 0.9331 0.9326 0.9245 0.923
3 0.9673 0.9669 0.8796 0.9723 0.9044 0.9243 0.9139 0.9215 0.9137 0.9104 0.9057 0.8995
4 0.9673 0.9669 0.8796 0.9723 0.8749 0.903 0.8856 0.897 0.8973 0.8912 0.884 0.8801
5 0.9673 0.9669 0.8796 0.9723 0.8444 0.882 0.8544 0.8675 0.8844 0.8726 0.8647 0.8615
6 0.9673 0.9669 0.8796 0.9723 0.8123 0.8572 0.824 0.8355 0.8715 0.857 0.846 0.8453
7 0.9673 0.9669 0.8796 0.9723 0.7779 0.8327 0.7916 0.8049 0.8599 0.8424 0.8303 0.8314
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.403668 0.40751 0.406656 0.40658 0.0502894 0.0501402 0.0531705 0.05323 0.654839 0.654999 0.655981 0.657194
1 0.411553 0.413656 0.410467 0.411666 0.0605093 0.0574014 0.0616628 0.0624245 0.670764 0.671248 0.672862 0.675631
2 0.412664 0.4141 0.417972 0.412485 0.0764619 0.0696777 0.0755108 0.0769719 0.68491 0.685501 0.68811 0.69195
3 0.41286 0.414108 0.430033 0.412557 0.0945023 0.0841159 0.0917475 0.0935722 0.697235 0.697954 0.70175 0.706033
4 0.412928 0.414108 0.430198 0.412559 0.113023 0.0994097 0.108795 0.111083 0.708013 0.708893 0.713984 0.718273
5 0.412937 0.414108 0.430199 0.412559 0.131267 0.114831 0.126082 0.128605 0.717541 0.718552 0.725043 0.729047
6 0.412937 0.414108 0.430199 0.412559 0.148966 0.13009 0.143144 0.145681 0.726042 0.727116 0.735079 0.738636
7 0.412937 0.414108 0.430199 0.412559 0.165997 0.144998 0.159629 0.161962 0.733677 0.73476 0.744282 0.747266
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.266264 0.267398 0.266584 0.266509 0.0740602 0.0734446 0.0756389 0.0757986 0.379938 0.380751 0.382924 0.383183
1 0.26758 0.268586 0.267785 0.267449 0.0787871 0.076552 0.0796463 0.0805345 0.387009 0.388317 0.39081 0.391429
2 0.267778 0.268689 0.273215 0.267621 0.0879414 0.0836189 0.0875788 0.0891107 0.394199 0.395836 0.39883 0.399681
3 0.267818 0.268691 0.277408 0.267632 0.0983289 0.0920365 0.0969103 0.0988525 0.400671 0.402536 0.406154 0.407013
4 0.267845 0.268691 0.277468 0.267632 0.108826 0.100847 0.106535 0.108903 0.406393 0.408426 0.412746 0.413463
5 0.267846 0.268691 0.277468 0.267632 0.118998 0.109568 0.116135 0.118739 0.411474 0.413609 0.418693 0.419158
6 0.267846 0.268691 0.277468 0.267632 0.128729 0.118038 0.125465 0.128158 0.416019 0.418186 0.424077 0.424228
7 0.267846 0.268691 0.277468 0.267632 0.137978 0.126183 0.134364 0.137013 0.420109 0.422257 0.42901 0.428787 
predictions_df_20
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.9499 0.9568 0.9586 0.9586 0.9046 0.9067 0.9143 0.9191 0.9523 0.9536 0.9533 0.953
1 0.9485 0.9467 0.9547 0.9579 0.9156 0.9184 0.9199 0.9247 0.942 0.9426 0.9424 0.9404
2 0.9486 0.9462 0.8688 0.9571 0.8963 0.9077 0.8931 0.9081 0.9256 0.9242 0.9235 0.9196
3 0.9485 0.9462 0.8652 0.957 0.8658 0.8847 0.8622 0.8771 0.907 0.9028 0.8986 0.8981
4 0.9487 0.9462 0.8652 0.957 0.8282 0.8601 0.8249 0.8415 0.8912 0.883 0.8773 0.8758
5 0.9486 0.9462 0.8652 0.957 0.7921 0.836 0.7892 0.8057 0.878 0.8633 0.8564 0.8562
6 0.9486 0.9462 0.8652 0.957 0.7551 0.8082 0.7532 0.768 0.8646 0.8504 0.8371 0.8382
7 0.9486 0.9462 0.8652 0.957 0.7192 0.7785 0.7229 0.7368 0.8532 0.837 0.8201 0.821
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.401566 0.407414 0.405025 0.405283 0.0789296 0.0810586 0.08523 0.0792877 0.655929 0.656125 0.656782 0.657778
1 0.412268 0.417075 0.41105 0.413413 0.0881912 0.0870752 0.0927642 0.0864279 0.672258 0.67298 0.674161 0.676794
2 0.414048 0.418045 0.41879 0.414256 0.10477 0.0998136 0.107025 0.100372 0.686313 0.687228 0.689412 0.693121
3 0.41427 0.418083 0.43078 0.414337 0.123663 0.114859 0.123549 0.116679 0.698515 0.699598 0.70297 0.707205
4 0.414344 0.418083 0.430994 0.414352 0.142811 0.130555 0.14087 0.133741 0.709182 0.710464 0.71514 0.719427
5 0.414371 0.418083 0.430995 0.414352 0.161364 0.146262 0.158243 0.150554 0.718586 0.720065 0.726134 0.73016
6 0.414374 0.418083 0.430995 0.414352 0.179078 0.161695 0.17533 0.167263 0.726985 0.72859 0.736191 0.739734
7 0.414373 0.418083 0.430995 0.414352 0.195942 0.176663 0.191698 0.183023 0.734581 0.736229 0.745468 0.748364
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.266632 0.268568 0.266769 0.266817 0.096705 0.0977197 0.099211 0.0954676 0.383635 0.384419 0.386474 0.386508
1 0.268284 0.270632 0.26824 0.268425 0.0986812 0.0982424 0.10099 0.0974408 0.388652 0.390058 0.392378 0.392812
2 0.268581 0.270878 0.273627 0.268597 0.106619 0.104053 0.107727 0.104377 0.395267 0.397107 0.399916 0.400614
3 0.268611 0.27088 0.277828 0.268615 0.116406 0.111715 0.116148 0.113008 0.401489 0.40362 0.407036 0.407791
4 0.268622 0.27088 0.277901 0.268621 0.126506 0.119959 0.125183 0.122126 0.407064 0.409393 0.413511 0.414143
5 0.268631 0.27088 0.277901 0.268621 0.136323 0.128257 0.134276 0.131077 0.412038 0.414495 0.419383 0.419772
6 0.26863 0.27088 0.277901 0.268621 0.145686 0.136368 0.143177 0.139941 0.416499 0.419018 0.424754 0.424806
7 0.26863 0.27088 0.277901 0.268621 0.154558 0.144223 0.151683 0.148283 0.420546 0.423061 0.429686 0.429347 
predictions_df_30
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.9211 0.9291 0.9324 0.9402 0.8484 0.8502 0.8554 0.8666 0.9482 0.9476 0.9488 0.9443
1 0.9209 0.9148 0.9279 0.941 0.8644 0.8687 0.862 0.8772 0.9404 0.9381 0.9383 0.9336
2 0.9209 0.9137 0.8489 0.9398 0.8443 0.856 0.8318 0.8577 0.9233 0.9164 0.9157 0.9127
3 0.9209 0.9136 0.8432 0.9395 0.8096 0.8276 0.7894 0.8196 0.9065 0.8974 0.8938 0.8907
4 0.9207 0.9136 0.8432 0.9395 0.7711 0.8001 0.7464 0.7771 0.8883 0.878 0.8711 0.869
5 0.9207 0.9136 0.8432 0.9395 0.7313 0.768 0.7085 0.7329 0.8737 0.8598 0.8522 0.8489
6 0.9207 0.9136 0.8432 0.9395 0.6921 0.7365 0.67 0.6965 0.8631 0.843 0.8338 0.829
7 0.9207 0.9136 0.8432 0.9395 0.6531 0.7059 0.6299 0.6613 0.8518 0.8294 0.8155 0.813
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.39972 0.408342 0.405548 0.404226 0.11174 0.116974 0.121919 0.107334 0.657462 0.657374 0.65801 0.658766
1 0.415414 0.423196 0.415446 0.414941 0.121169 0.123135 0.129149 0.113681 0.67426 0.674851 0.676048 0.678462
2 0.417902 0.424844 0.423254 0.41642 0.138609 0.136851 0.143653 0.127756 0.688287 0.689122 0.691391 0.694824
3 0.418224 0.424972 0.434709 0.416567 0.158104 0.152708 0.160389 0.143935 0.700306 0.701341 0.704828 0.708781
4 0.418263 0.424999 0.435005 0.416568 0.177548 0.168921 0.177692 0.161158 0.710796 0.712037 0.716848 0.720966
5 0.418301 0.425009 0.435006 0.416569 0.196173 0.184893 0.194883 0.177825 0.720063 0.721488 0.727718 0.731778
6 0.4183 0.425009 0.435006 0.416569 0.213725 0.200461 0.211572 0.194125 0.728359 0.729941 0.737603 0.741435
7 0.4183 0.425009 0.435006 0.416569 0.230168 0.215349 0.22762 0.208939 0.735867 0.737552 0.746705 0.750084
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.267842 0.270801 0.26843 0.267434 0.120138 0.12272 0.122911 0.114469 0.388009 0.388508 0.39054 0.390494
1 0.270285 0.274225 0.270686 0.269442 0.120797 0.122337 0.123651 0.115008 0.390834 0.392081 0.394363 0.39468
2 0.270678 0.274635 0.275886 0.269776 0.127935 0.127603 0.129675 0.121056 0.396839 0.398588 0.401352 0.401922
3 0.270731 0.274659 0.279969 0.269816 0.137168 0.134829 0.137495 0.128866 0.40276 0.40483 0.408219 0.408853
4 0.270733 0.274666 0.280069 0.269817 0.146806 0.142702 0.145924 0.137546 0.408139 0.410429 0.414531 0.41511
5 0.270737 0.274668 0.280069 0.269817 0.156183 0.15066 0.154464 0.14603 0.41297 0.415401 0.420279 0.420725
6 0.270737 0.274668 0.280069 0.269817 0.165086 0.158488 0.162817 0.154366 0.417325 0.419855 0.425514 0.425768
7 0.270737 0.274668 0.280069 0.269817 0.173449 0.165975 0.170892 0.161958 0.421281 0.423857 0.430333 0.430287 
predictions_df_40
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.8753 0.8893 0.8957 0.9101 0.7812 0.7859 0.7806 0.8153 0.9353 0.9358 0.9319 0.9333
1 0.8747 0.8653 0.8894 0.9099 0.8046 0.8008 0.788 0.8272 0.9279 0.9241 0.9224 0.9264
2 0.8746 0.8637 0.8157 0.9088 0.7735 0.7796 0.7519 0.7913 0.9086 0.9056 0.9029 0.9019
3 0.8746 0.8635 0.8089 0.9087 0.7385 0.7467 0.7113 0.7464 0.8911 0.8853 0.8794 0.8794
4 0.8744 0.8635 0.8089 0.9087 0.6943 0.7145 0.6656 0.7029 0.8731 0.8642 0.8552 0.8557
5 0.8744 0.8635 0.8089 0.9087 0.6506 0.6765 0.6273 0.6593 0.8572 0.8453 0.8349 0.8365
6 0.8744 0.8635 0.8089 0.9087 0.6152 0.6404 0.594 0.6236 0.8454 0.8291 0.8164 0.8202
7 0.8744 0.8635 0.8089 0.9087 0.5783 0.6099 0.5583 0.5879 0.8334 0.8166 0.7994 0.8057
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.398473 0.409486 0.405093 0.401478 0.14846 0.157898 0.162714 0.138039 0.659447 0.659365 0.659623 0.660434
1 0.419404 0.431752 0.421153 0.417776 0.158797 0.16522 0.16925 0.143112 0.676798 0.677446 0.678267 0.680678
2 0.423355 0.434253 0.429555 0.420008 0.177164 0.180584 0.183297 0.156712 0.69081 0.691768 0.693695 0.697138
3 0.4241 0.434428 0.440935 0.420237 0.197046 0.19751 0.199288 0.172501 0.702673 0.703959 0.707071 0.711045
4 0.424197 0.434451 0.441425 0.420242 0.216432 0.214307 0.215952 0.188673 0.713018 0.714634 0.719018 0.723076
5 0.424226 0.434451 0.441435 0.420242 0.234741 0.230496 0.232245 0.204733 0.72216 0.724037 0.72983 0.733607
6 0.424226 0.434451 0.441435 0.420242 0.251845 0.245859 0.247871 0.22013 0.730337 0.732413 0.739692 0.742942
7 0.424226 0.434451 0.441435 0.420242 0.267764 0.260389 0.262877 0.23505 0.737745 0.739952 0.748713 0.751345
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.269725 0.274089 0.270518 0.268207 0.144321 0.149093 0.147213 0.133752 0.393013 0.393415 0.395335 0.395305
1 0.273146 0.279165 0.274277 0.271264 0.144703 0.14877 0.146961 0.13298 0.393505 0.394711 0.39682 0.397065
2 0.273808 0.279828 0.279328 0.271766 0.151463 0.154175 0.152197 0.138041 0.398764 0.400553 0.403112 0.403616
3 0.273946 0.279873 0.283497 0.271827 0.160222 0.161354 0.159135 0.145039 0.404331 0.406513 0.409697 0.41026
4 0.273955 0.279874 0.283655 0.271828 0.169336 0.169014 0.166814 0.152664 0.409504 0.411955 0.41587 0.416319
5 0.273957 0.279874 0.283657 0.271828 0.178181 0.176635 0.174573 0.160458 0.414207 0.41682 0.421542 0.421735
6 0.273957 0.279874 0.283657 0.271828 0.186554 0.18397 0.182121 0.168074 0.418475 0.421172 0.42673 0.426581
7 0.273957 0.279874 0.283657 0.271828 0.194395 0.190951 0.189483 0.175533 0.422371 0.42509 0.431463 0.430959 
predictions_df_50
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.8104 0.843 0.8465 0.8637 0.7102 0.7038 0.6837 0.7456 0.9231 0.9193 0.915 0.9178
1 0.8124 0.8109 0.835 0.8633 0.7185 0.715 0.6927 0.7507 0.9153 0.9117 0.9092 0.9101
2 0.8138 0.8083 0.7697 0.8624 0.6901 0.6885 0.6576 0.715 0.8945 0.8888 0.8862 0.8876
3 0.8137 0.8082 0.7614 0.8623 0.6518 0.6544 0.6096 0.6697 0.8753 0.8672 0.8625 0.8648
4 0.8135 0.8082 0.7613 0.8623 0.6091 0.6164 0.5704 0.6244 0.8545 0.8457 0.8368 0.8417
5 0.8135 0.8082 0.7613 0.8623 0.5705 0.585 0.5335 0.584 0.8388 0.8271 0.8157 0.8219
6 0.8135 0.8082 0.7613 0.8623 0.5306 0.5501 0.4981 0.5454 0.8235 0.8116 0.799 0.8043
7 0.8135 0.8082 0.7613 0.8623 0.5013 0.5231 0.4696 0.509 0.8113 0.7952 0.7836 0.7894
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.399107 0.412362 0.407298 0.402069 0.188267 0.201783 0.208569 0.177367 0.662679 0.662416 0.662516 0.66272
1 0.427134 0.442528 0.428738 0.425446 0.199843 0.210575 0.213153 0.179138 0.680583 0.681436 0.681745 0.683465
2 0.43352 0.44571 0.437533 0.428058 0.219119 0.227662 0.225993 0.191304 0.69458 0.695877 0.697247 0.699886
3 0.434552 0.446022 0.448088 0.428288 0.239303 0.245776 0.241007 0.206327 0.706262 0.707904 0.710476 0.713526
4 0.434763 0.446023 0.448634 0.428298 0.258573 0.262979 0.256039 0.222903 0.716433 0.718417 0.722272 0.725372
5 0.434775 0.446023 0.448651 0.428298 0.276493 0.278979 0.271045 0.238192 0.725454 0.727737 0.732927 0.735813
6 0.434776 0.446023 0.448651 0.428298 0.292947 0.293865 0.285361 0.253124 0.733536 0.736051 0.742591 0.745091
7 0.434776 0.446023 0.448651 0.428298 0.30814 0.307676 0.298997 0.266585 0.74079 0.743516 0.751433 0.753417
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.273311 0.278311 0.274183 0.270802 0.169088 0.175511 0.172673 0.156256 0.398883 0.399074 0.400948 0.400674
1 0.278325 0.2854 0.278733 0.275651 0.169797 0.175721 0.170949 0.153344 0.397079 0.398302 0.400182 0.400037
2 0.279431 0.286133 0.283535 0.276146 0.176476 0.181661 0.175267 0.157278 0.4015 0.403445 0.405709 0.405773
3 0.279604 0.28621 0.287424 0.276198 0.184892 0.189076 0.181465 0.163496 0.406656 0.409021 0.411898 0.411997
4 0.279643 0.286209 0.287614 0.276202 0.193521 0.196615 0.188107 0.170984 0.411577 0.414193 0.417807 0.4178
5 0.279641 0.286209 0.287617 0.276202 0.201823 0.203873 0.195059 0.178132 0.416094 0.418878 0.423263 0.42306
6 0.279641 0.286209 0.287617 0.276202 0.209588 0.210755 0.201787 0.185324 0.420222 0.423102 0.428268 0.427808
7 0.279641 0.286209 0.287617 0.276202 0.216819 0.217192 0.208311 0.191876 0.423984 0.426912 0.432879 0.432108 
predictions_df_60
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.7325 0.771 0.776 0.8011 0.6279 0.6315 0.5911 0.6701 0.894 0.8908 0.897 0.8923
1 0.7312 0.7362 0.762 0.8056 0.6301 0.632 0.5976 0.6806 0.8907 0.8868 0.8897 0.8864
2 0.7315 0.7338 0.7047 0.802 0.5931 0.6025 0.5561 0.6393 0.8749 0.8673 0.8659 0.866
3 0.7314 0.7338 0.6957 0.8018 0.5556 0.5568 0.5132 0.5867 0.856 0.8473 0.8416 0.8418
4 0.7314 0.7338 0.6958 0.8019 0.5205 0.5232 0.4763 0.5415 0.8388 0.8236 0.8136 0.8211
5 0.7314 0.7338 0.6958 0.8019 0.485 0.4878 0.4473 0.5031 0.8222 0.8033 0.7926 0.8003
6 0.7314 0.7338 0.6958 0.8019 0.4497 0.4593 0.414 0.4712 0.8088 0.7879 0.7766 0.781
7 0.7314 0.7338 0.6958 0.8019 0.4253 0.4373 0.3911 0.4435 0.7956 0.7729 0.7589 0.7675
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.404246 0.415999 0.41066 0.403715 0.231558 0.247913 0.25725 0.218518 0.667022 0.666319 0.666325 0.666299
1 0.439251 0.454707 0.441453 0.43463 0.245325 0.257559 0.259574 0.216983 0.685609 0.686234 0.68646 0.688047
2 0.447135 0.458615 0.450368 0.438785 0.266171 0.275057 0.270565 0.226807 0.699624 0.700893 0.702237 0.704688
3 0.448309 0.458932 0.460154 0.43914 0.286896 0.292735 0.283902 0.240673 0.711058 0.712878 0.715483 0.718264
4 0.44842 0.459006 0.460914 0.439176 0.30592 0.309111 0.297882 0.255848 0.721024 0.723327 0.727186 0.729996
5 0.448426 0.459007 0.460917 0.439178 0.323124 0.324244 0.311406 0.269943 0.729871 0.732602 0.737667 0.740295
6 0.448426 0.459007 0.460918 0.439179 0.338636 0.338282 0.324746 0.283565 0.7378 0.740881 0.747155 0.749456
7 0.448426 0.459007 0.460918 0.439179 0.35279 0.351148 0.337137 0.296849 0.745 0.748318 0.755824 0.75769
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.278889 0.283678 0.279278 0.274848 0.194937 0.20206 0.198694 0.178885 0.405696 0.405674 0.407456 0.407166
1 0.285416 0.292182 0.286166 0.28113 0.196622 0.202466 0.195405 0.173956 0.401657 0.402645 0.404434 0.404289
2 0.286774 0.293094 0.290468 0.281981 0.203896 0.208399 0.198687 0.17643 0.405137 0.406953 0.409125 0.409213
3 0.286984 0.293162 0.294066 0.282047 0.212328 0.215372 0.203886 0.181793 0.409787 0.412143 0.414948 0.415057
4 0.286994 0.293173 0.294309 0.28205 0.220568 0.22231 0.209865 0.18834 0.414423 0.417128 0.420616 0.420642
5 0.286994 0.293173 0.29431 0.282049 0.228229 0.228985 0.21592 0.194715 0.41876 0.421692 0.425873 0.425743
6 0.286994 0.293173 0.29431 0.282049 0.235269 0.235262 0.222059 0.201088 0.422755 0.425808 0.430711 0.430364
7 0.286994 0.293173 0.29431 0.282049 0.241747 0.241094 0.227858 0.207406 0.426437 0.429525 0.435173 0.434545 
predictions_df_70
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.6424 0.6924 0.6892 0.7254 0.5432 0.5548 0.4819 0.5838 0.8528 0.8516 0.8563 0.8563
1 0.6419 0.656 0.6744 0.7251 0.5387 0.5416 0.483 0.5751 0.8578 0.8569 0.8557 0.8592
2 0.6402 0.6537 0.627 0.7218 0.5068 0.5073 0.4498 0.5368 0.8432 0.8376 0.8353 0.8382
3 0.6403 0.6535 0.6169 0.7215 0.4674 0.466 0.4212 0.495 0.8238 0.8165 0.8108 0.8121
4 0.6405 0.6535 0.6168 0.7215 0.4309 0.4353 0.4013 0.4569 0.8041 0.794 0.7886 0.7902
5 0.6405 0.6535 0.6168 0.7215 0.3974 0.4059 0.3765 0.4213 0.7907 0.7759 0.7668 0.7698
6 0.6404 0.6535 0.6168 0.7215 0.3705 0.3828 0.357 0.3957 0.778 0.7612 0.746 0.7532
7 0.6404 0.6535 0.6168 0.7215 0.3471 0.3588 0.3324 0.3718 0.7669 0.7474 0.727 0.7363
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.409518 0.421532 0.415563 0.40436 0.274594 0.293222 0.30836 0.272889 0.673847 0.672533 0.672543 0.671785
1 0.450838 0.467912 0.454492 0.446293 0.289239 0.302874 0.306156 0.263908 0.693604 0.693438 0.693705 0.694767
2 0.461699 0.472804 0.464168 0.452165 0.310558 0.32057 0.313881 0.268382 0.70793 0.708225 0.709565 0.7119
3 0.4633 0.473207 0.473487 0.452887 0.331274 0.337965 0.324967 0.278823 0.719135 0.719926 0.722345 0.725396
4 0.463535 0.473229 0.474218 0.452936 0.349984 0.353662 0.336969 0.292706 0.72874 0.730099 0.733532 0.736902
5 0.463584 0.473244 0.474254 0.452937 0.366617 0.36777 0.348859 0.30636 0.737248 0.739174 0.743617 0.74701
6 0.463581 0.473244 0.474254 0.452937 0.381423 0.380516 0.36038 0.319061 0.744921 0.747312 0.752791 0.756019
7 0.463592 0.473244 0.474254 0.452937 0.394562 0.392138 0.371188 0.33078 0.7519 0.754596 0.76122 0.764074
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.284931 0.289298 0.285147 0.279101 0.21964 0.227256 0.225593 0.207462 0.414186 0.413766 0.415476 0.415093
1 0.292974 0.299768 0.293712 0.288054 0.221828 0.22747 0.219427 0.198619 0.408246 0.408668 0.410494 0.410129
2 0.294863 0.300829 0.297768 0.289291 0.229319 0.233484 0.221105 0.198323 0.410834 0.412022 0.414168 0.414183
3 0.295097 0.300896 0.301319 0.289454 0.237613 0.240273 0.225095 0.201782 0.414908 0.416654 0.419298 0.41956
4 0.295118 0.3009 0.301547 0.289456 0.245487 0.246804 0.230037 0.20747 0.419106 0.421252 0.424477 0.42481
5 0.295127 0.300903 0.30156 0.289456 0.252637 0.252873 0.235174 0.213412 0.423103 0.425542 0.429389 0.429665
6 0.295126 0.300903 0.30156 0.289456 0.25907 0.258429 0.240343 0.219155 0.426848 0.429464 0.433979 0.434099
7 0.295126 0.300903 0.30156 0.289456 0.264794 0.263503 0.245247 0.224557 0.430332 0.433022 0.438247 0.438124 
predictions_df_80
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.5598 0.5938 0.6045 0.6312 0.4721 0.4641 0.3981 0.4879 0.8012 0.8067 0.7957 0.8013
1 0.5524 0.5583 0.5864 0.6295 0.4611 0.4453 0.394 0.4805 0.8048 0.8051 0.8031 0.8116
2 0.5525 0.5574 0.5507 0.6242 0.428 0.412 0.3734 0.4474 0.7898 0.7879 0.7795 0.7899
3 0.5525 0.5572 0.5419 0.6233 0.3923 0.3819 0.3518 0.409 0.7744 0.7685 0.7588 0.7653
4 0.5525 0.5572 0.5418 0.6232 0.358 0.354 0.3388 0.3857 0.7556 0.7484 0.7366 0.7438
5 0.5525 0.5572 0.5418 0.6232 0.3344 0.3333 0.3207 0.3563 0.7429 0.729 0.712 0.7236
6 0.5525 0.5572 0.5418 0.6232 0.3149 0.3138 0.3039 0.3312 0.7291 0.7106 0.6918 0.7045
7 0.5525 0.5572 0.5418 0.6231 0.2959 0.2998 0.2849 0.3122 0.7191 0.6955 0.6763 0.6912
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.419228 0.431738 0.423274 0.412763 0.319946 0.341009 0.370053 0.34326 0.683892 0.682911 0.682496 0.679958
1 0.464674 0.485127 0.468674 0.464941 0.335582 0.349063 0.361413 0.322244 0.705116 0.705698 0.70505 0.704498
2 0.476911 0.490661 0.478811 0.473158 0.357098 0.365699 0.365443 0.317128 0.719751 0.72118 0.721379 0.72215
3 0.478827 0.491093 0.487049 0.473993 0.37729 0.381791 0.373641 0.322666 0.730758 0.73288 0.734113 0.735508
4 0.479061 0.49113 0.487817 0.474046 0.394982 0.39596 0.383487 0.334134 0.740104 0.742847 0.745071 0.746707
5 0.479091 0.49113 0.48785 0.474049 0.410116 0.408413 0.393202 0.345689 0.748375 0.751608 0.754888 0.756446
6 0.479098 0.49113 0.487851 0.474049 0.423287 0.419525 0.402857 0.357512 0.755801 0.759347 0.763788 0.765078
7 0.479098 0.49113 0.487851 0.474057 0.434632 0.429435 0.41203 0.368105 0.762519 0.766218 0.771913 0.772799
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.292446 0.297199 0.292244 0.286975 0.245538 0.25351 0.257629 0.243098 0.424318 0.424194 0.425794 0.424643
1 0.300931 0.309245 0.301885 0.298563 0.248221 0.252652 0.247362 0.228293 0.416847 0.417696 0.419164 0.417822
2 0.303023 0.310386 0.305633 0.300316 0.255947 0.258143 0.247326 0.223467 0.418508 0.420294 0.421883 0.420916
3 0.303308 0.310471 0.308676 0.300544 0.263993 0.264242 0.249984 0.224517 0.422012 0.424386 0.426409 0.42571
4 0.303349 0.310479 0.308921 0.30056 0.271218 0.269906 0.253812 0.228922 0.425803 0.428543 0.431158 0.430542
5 0.303353 0.310479 0.308933 0.300561 0.277285 0.275044 0.257836 0.233653 0.429486 0.432443 0.435739 0.435058
6 0.303353 0.310479 0.308933 0.300561 0.282522 0.279676 0.262041 0.238841 0.432951 0.436005 0.440057 0.439192
7 0.303352 0.310479 0.308933 0.300565 0.287014 0.283811 0.266161 0.243621 0.436183 0.439222 0.444081 0.442969 
predictions_df_90
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.4652 0.4935 0.5065 0.5292 0.3957 0.3788 0.314 0.4017 0.7071 0.7092 0.7051 0.7246
1 0.461 0.4641 0.4886 0.5257 0.3832 0.3678 0.3143 0.3908 0.7148 0.7171 0.7135 0.7304
2 0.4608 0.4613 0.4613 0.5226 0.3501 0.3402 0.2969 0.3603 0.7032 0.7025 0.7004 0.7139
3 0.4609 0.4615 0.4539 0.5223 0.3198 0.3169 0.2837 0.3221 0.6893 0.6838 0.681 0.6914
4 0.4608 0.4616 0.4539 0.5222 0.2937 0.2955 0.2724 0.2999 0.675 0.6668 0.6613 0.6706
5 0.4608 0.4616 0.4539 0.5222 0.2748 0.2783 0.2565 0.2813 0.6632 0.6484 0.6415 0.654
6 0.4608 0.4616 0.4539 0.5222 0.2591 0.2617 0.2488 0.2639 0.6504 0.6314 0.6231 0.6381
7 0.4608 0.4616 0.4539 0.5222 0.2467 0.2532 0.235 0.2494 0.6422 0.6171 0.61 0.6224
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.427204 0.437576 0.428068 0.421905 0.363935 0.385668 0.452028 0.436702 0.698825 0.697489 0.695876 0.691769
1 0.476592 0.499122 0.481791 0.48391 0.378551 0.390117 0.43303 0.39795 0.722475 0.722666 0.720736 0.718654
2 0.489934 0.505976 0.493166 0.49329 0.398947 0.404578 0.431089 0.37546 0.738333 0.739211 0.738099 0.737462
3 0.49196 0.506606 0.499699 0.494142 0.417719 0.419032 0.4349 0.371568 0.74965 0.751022 0.750958 0.751077
4 0.492389 0.506711 0.500468 0.494221 0.433353 0.431877 0.441362 0.379185 0.758926 0.760765 0.761751 0.762213
5 0.492441 0.506713 0.500503 0.494244 0.446655 0.443176 0.448601 0.389034 0.766981 0.7692 0.771273 0.771781
6 0.492441 0.506713 0.500503 0.494247 0.458022 0.453166 0.455825 0.39855 0.774132 0.776615 0.779837 0.780181
7 0.492441 0.506713 0.500503 0.494248 0.467886 0.461968 0.463112 0.407242 0.780542 0.783188 0.78762 0.787625
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.299068 0.303071 0.298303 0.295683 0.270353 0.277639 0.299549 0.28932 0.437361 0.436989 0.437882 0.436412
1 0.307824 0.317106 0.309481 0.308793 0.27244 0.274363 0.282411 0.266012 0.429087 0.429509 0.430412 0.428378
2 0.309916 0.318569 0.313115 0.310672 0.279775 0.278832 0.279827 0.25328 0.430209 0.431449 0.432438 0.430719
3 0.310215 0.318698 0.315552 0.310885 0.286985 0.284098 0.280559 0.249867 0.433282 0.435039 0.436428 0.435013
4 0.310294 0.318725 0.315785 0.310915 0.292798 0.289071 0.282811 0.252309 0.436695 0.438777 0.440737 0.439462
5 0.310299 0.318725 0.315796 0.310923 0.297606 0.293576 0.285633 0.256194 0.440053 0.442291 0.444947 0.443667
6 0.310299 0.318725 0.315796 0.310925 0.301603 0.297615 0.288647 0.260149 0.443236 0.445504 0.448934 0.447544
7 0.310299 0.318725 0.315796 0.310925 0.305162 0.301156 0.291791 0.263878 0.446208 0.448432 0.452657 0.45107 
predictions_df_100
Accuracy over iterations evaluations_feature_classifier
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.3784 0.4094 0.4158 0.4407 0.3254 0.3107 0.2505 0.3128 0.5857 0.5907 0.5885 0.6129
1 0.3693 0.3836 0.3974 0.4326 0.3141 0.2984 0.246 0.2982 0.597 0.6009 0.596 0.6273
2 0.3681 0.3827 0.3811 0.4304 0.288 0.2792 0.2367 0.2759 0.5942 0.5916 0.5907 0.6154
3 0.3684 0.3823 0.3729 0.43 0.2631 0.258 0.2292 0.2505 0.5812 0.5808 0.5753 0.5984
4 0.3683 0.3824 0.3729 0.4298 0.2384 0.2463 0.2215 0.2344 0.5686 0.5661 0.5623 0.5803
5 0.3682 0.3824 0.3729 0.4298 0.2252 0.2338 0.2085 0.2248 0.5569 0.5537 0.5435 0.5652
6 0.3682 0.3824 0.3729 0.4298 0.2126 0.2248 0.2019 0.2153 0.5497 0.5407 0.5258 0.5547
7 0.3682 0.3824 0.3729 0.4298 0.2035 0.2175 0.1976 0.2083 0.5433 0.5298 0.5138 0.5419
Loss over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.440462 0.448423 0.437717 0.450613 0.407329 0.434543 0.55697 0.555693 0.721071 0.719842 0.71808 0.710819
1 0.491401 0.510573 0.498156 0.526702 0.420339 0.434074 0.525217 0.494462 0.748418 0.748178 0.746051 0.741466
2 0.507672 0.517494 0.508688 0.538066 0.439741 0.446138 0.516743 0.444587 0.766187 0.765932 0.764916 0.76216
3 0.510319 0.518058 0.514444 0.539305 0.457017 0.458949 0.516149 0.424745 0.778076 0.777833 0.778057 0.776047
4 0.510722 0.51814 0.515555 0.539533 0.47068 0.470507 0.519025 0.425091 0.787433 0.78732 0.788656 0.78689
5 0.510809 0.518149 0.515586 0.539553 0.482153 0.480636 0.523211 0.430893 0.795335 0.795433 0.797878 0.796006
6 0.510852 0.518149 0.515587 0.53956 0.491912 0.489408 0.528222 0.43841 0.802233 0.802535 0.806092 0.803902
7 0.510853 0.518149 0.515587 0.539561 0.500285 0.496997 0.533356 0.446601 0.808382 0.808806 0.813429 0.810868
MAE over iterations autoencoder
normal_dim 256 10_Targets normal_dim 128 10_Targets normal_dim 64 10_Targets normal_dim 32 10_Targets normal_dim 256 Mnist normal_dim 128 Mnist normal_dim 64 Mnist normal_dim 32 Mnist normal_dim 256 Noisy normal_dim 128 Noisy normal_dim 64 Noisy normal_dim 32 Noisy
0 0.3092 0.309525 0.306122 0.313413 0.295574 0.304131 0.35312 0.347392 0.453886 0.453995 0.454277 0.451949
1 0.316775 0.323071 0.318368 0.331185 0.296274 0.297317 0.327295 0.313752 0.44592 0.446119 0.446861 0.443789
2 0.319462 0.324482 0.321228 0.33349 0.303093 0.300689 0.321828 0.288579 0.446974 0.447419 0.448566 0.445682
3 0.319857 0.324584 0.323429 0.333785 0.309216 0.305219 0.320593 0.277792 0.449823 0.450408 0.452136 0.44944
4 0.319921 0.324599 0.323754 0.333865 0.313521 0.309543 0.321155 0.276645 0.452979 0.453624 0.455994 0.453374
5 0.319939 0.324601 0.323765 0.333871 0.316935 0.313407 0.322482 0.278347 0.456058 0.456713 0.459779 0.457109
6 0.319943 0.324601 0.323765 0.333873 0.319834 0.316782 0.324386 0.281305 0.458959 0.459584 0.463371 0.460551
7 0.319943 0.324601 0.323765 0.333873 0.322452 0.319674 0.326474 0.284777 0.46167 0.462214 0.466714 0.463703